{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T02:21:11Z","timestamp":1770517271130,"version":"3.49.0"},"reference-count":54,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,1,24]],"date-time":"2020-01-24T00:00:00Z","timestamp":1579824000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010665","name":"H2020 Marie Sk\u0142odowska-Curie Actions","doi-asserted-by":"publisher","award":["765057"],"award-info":[{"award-number":["765057"]}],"id":[{"id":"10.13039\/100010665","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Smart materials are promising technologies for reducing the instrumentation cost required to continuously monitor road infrastructures, by transforming roadways into multifunctional elements capable of self-sensing. This study investigates a novel algorithm empowering smart pavements with weigh-in-motion (WIM) characterization capabilities. The application domain of interest is a cementitious-based smart pavement installed on a bridge over separate sections. Each section transduces axial strain provoked by the passage of a vehicle into a measurable change in electrical resistance arising from the piezoresistive effect of the smart material. The WIM characterization algorithm is as follows. First, basis signals from axles are generated from a finite element model of the structure equipped with the smart pavement and subjected to given vehicle loads. Second, the measured signal is matched by finding the number and weights of appropriate basis signals that would minimize the error between the numerical and measured signals, yielding information on the vehicle\u2019s number of axles and weight per axle, therefore enabling vehicle classification capabilities. Third, the temporal correlation of the measured signals are compared across smart pavement sections to determine the vehicle weight. The proposed algorithm is validated numerically using three types of trucks defined by the Eurocodes. Results demonstrate the capability of the algorithm at conducting WIM characterization, even when two different trucks are driving in different directions across the same pavement sections. Then, a noise study is conducted, and the results conclude that a given smart pavement section operating with less than 5% noise on measurements could yield good WIM characterization results.<\/jats:p>","DOI":"10.3390\/s20030659","type":"journal-article","created":{"date-parts":[[2020,1,24]],"date-time":"2020-01-24T11:01:00Z","timestamp":1579863660000},"page":"659","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["A Weigh-in-Motion Characterization Algorithm for Smart Pavements Based on Conductive Cementitious Materials"],"prefix":"10.3390","volume":"20","author":[{"given":"Hasan Borke","family":"Birgin","sequence":"first","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Perugia, via Goffredo Duranti 93, 06125 Perugia, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0601-9664","authenticated-orcid":false,"given":"Simon","family":"Laflamme","sequence":"additional","affiliation":[{"name":"Department of Civil, Construction and Environmental Engineering, Iowa State University, Ames, IA 50011, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2928-1961","authenticated-orcid":false,"given":"Antonella","family":"D\u2019Alessandro","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Perugia, via Goffredo Duranti 93, 06125 Perugia, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5557-144X","authenticated-orcid":false,"given":"Enrique","family":"Garcia-Macias","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Perugia, via Goffredo Duranti 93, 06125 Perugia, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5044-8482","authenticated-orcid":false,"given":"Filippo","family":"Ubertini","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Perugia, via Goffredo Duranti 93, 06125 Perugia, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2020,1,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.iatssr.2010.06.003","article-title":"Improving truck safety: Potential of weigh-in-motion technology","volume":"34","author":"Jacob","year":"2010","journal-title":"IATSS Res."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.compstruc.2012.09.002","article-title":"Fatigue reliability assessment of steel bridge details integrating weigh-in-motion data and probabilistic finite element analysis","volume":"112","author":"Guo","year":"2012","journal-title":"Comput. 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